Describing CO2-Absorbent Propertiesin AspenPlus®

Jasper A. Ros; Derk W.F. Brilman; I. M. Bernhardsen; H. Knuutila

doi:10.1016/B978-0-12-818634-3.50182-X

Describing CO₂-Absorbent Propertiesin AspenPlus®

Jasper A. Ros, Derk W.F. Brilman, I. M. Bernhardsen, H. Knuutila^*

^*Corresponding author for this work

Sustainable Process Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

2 Citations (Scopus)

Abstract

For the modelling of novel solvent systemsfor CO₂-capture in AspenPlus®, data fitting of physical-chemical properties is needed. In this work the challenges and results are presented for fitting such experimental data for aqueous solutions of 2-(diethylamino) ethanol (DEEA) and 3-(methylamino)propylamine (MAPA). Without CO₂ present, the default regression tool of AspenPlus® gave good data fits for the binary systems H₂O-MAPA and H₂O-DEEA. In the presence of CO₂, regression of parameters was not successful and an additional Particle Swarm Optimization (PSO) algorithm was needed to determine the many molecule-ion parameters for the ELECNRTL model. With this, for DEEA a good fit to experimental data has been obtained, whereas for MAPA, due to the high number of ionic species, the results were still not satisfactory. To resolve this, independent measurement of equilibrium constants for the ionic equilibria is recommended.

Original language	English
Title of host publication	Computer Aided Chemical Engineering
Publisher	Elsevier
Pages	1087-1092
Number of pages	6
Volume	46
ISBN (Print)	978-0-12-819939-8
DOIs	https://doi.org/10.1016/B978-0-12-818634-3.50182-X
Publication status	Published - 1 Jan 2019

Publication series

Name	Computer Aided Chemical Engineering
Volume	46
ISSN (Print)	1570-7946

Keywords

CO capture
novel solvents
regression
thermodynamic modelling
CO2 capture

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/B978-0-12-818634-3.50182-X

Cite this

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title = "Describing CO2-Absorbent Propertiesin AspenPlus{\textregistered}",

abstract = "For the modelling of novel solvent systemsfor CO2-capture in AspenPlus{\textregistered}, data fitting of physical-chemical properties is needed. In this work the challenges and results are presented for fitting such experimental data for aqueous solutions of 2-(diethylamino) ethanol (DEEA) and 3-(methylamino)propylamine (MAPA). Without CO2 present, the default regression tool of AspenPlus{\textregistered} gave good data fits for the binary systems H2O-MAPA and H2O-DEEA. In the presence of CO2, regression of parameters was not successful and an additional Particle Swarm Optimization (PSO) algorithm was needed to determine the many molecule-ion parameters for the ELECNRTL model. With this, for DEEA a good fit to experimental data has been obtained, whereas for MAPA, due to the high number of ionic species, the results were still not satisfactory. To resolve this, independent measurement of equilibrium constants for the ionic equilibria is recommended.",

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author = "Ros, {Jasper A.} and Brilman, {Derk W.F.} and Bernhardsen, {I. M.} and H. Knuutila",

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T1 - Describing CO2-Absorbent Propertiesin AspenPlus®

AU - Ros, Jasper A.

AU - Brilman, Derk W.F.

AU - Bernhardsen, I. M.

AU - Knuutila, H.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - For the modelling of novel solvent systemsfor CO2-capture in AspenPlus®, data fitting of physical-chemical properties is needed. In this work the challenges and results are presented for fitting such experimental data for aqueous solutions of 2-(diethylamino) ethanol (DEEA) and 3-(methylamino)propylamine (MAPA). Without CO2 present, the default regression tool of AspenPlus® gave good data fits for the binary systems H2O-MAPA and H2O-DEEA. In the presence of CO2, regression of parameters was not successful and an additional Particle Swarm Optimization (PSO) algorithm was needed to determine the many molecule-ion parameters for the ELECNRTL model. With this, for DEEA a good fit to experimental data has been obtained, whereas for MAPA, due to the high number of ionic species, the results were still not satisfactory. To resolve this, independent measurement of equilibrium constants for the ionic equilibria is recommended.

AB - For the modelling of novel solvent systemsfor CO2-capture in AspenPlus®, data fitting of physical-chemical properties is needed. In this work the challenges and results are presented for fitting such experimental data for aqueous solutions of 2-(diethylamino) ethanol (DEEA) and 3-(methylamino)propylamine (MAPA). Without CO2 present, the default regression tool of AspenPlus® gave good data fits for the binary systems H2O-MAPA and H2O-DEEA. In the presence of CO2, regression of parameters was not successful and an additional Particle Swarm Optimization (PSO) algorithm was needed to determine the many molecule-ion parameters for the ELECNRTL model. With this, for DEEA a good fit to experimental data has been obtained, whereas for MAPA, due to the high number of ionic species, the results were still not satisfactory. To resolve this, independent measurement of equilibrium constants for the ionic equilibria is recommended.

KW - CO capture

KW - novel solvents

KW - regression

KW - thermodynamic modelling

KW - CO2 capture

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